/ Glossary
The AI search glossary
The vocabulary of AI search and answer engine optimization, defined in plain English and cross-linked. Start anywhere.
Core disciplines
- Answer Engine OptimizationAEO
- The practice of measuring and improving how often AI answer engines mention and cite your brand.
- Generative Engine OptimizationGEO, Generative SEO
- Optimizing content to appear inside AI-generated answers. Largely a synonym for AEO.
- LLMOLLM Optimization, LLM SEO
- Large language model optimization: another name for the work of getting cited in AI answers.
- AI visibility
- How present your brand is across AI answers: how often it is mentioned, cited, and described accurately.
Where AI answers appear
- Answer engine
- A system that responds to a question with a synthesized answer rather than a page of links.
- AI search engine
- A search product that returns AI-written answers with citations instead of a ranked list.
- Google AI Overviews
- AI-generated summaries Google shows above traditional results for many queries, built on its Gemini models.
- Google AI Mode
- Google's full conversational search experience, a dedicated AI answer surface separate from AI Overviews.
- ChatGPT Search
- ChatGPT's web-browsing mode, which retrieves live pages and cites them in its answers.
What to measure
- AI citation
- A source link an AI answer attributes information to. The clearest signal that your content shaped the answer.
- Brand mention
- Any time an AI answer names your brand, whether or not it links to you.
- Share of voice
- How often AI engines mention your brand versus competitors across a set of prompts.
- Prompt volume
- The number of prompts an engine is queried with when tracking visibility. Tools often meter usage by it.
- Prompt trackingPrompt monitoring, Prompt set
- Running a fixed set of prompts across AI engines on a schedule to monitor how your brand appears over time.
- AI visibility score
- An aggregate metric rolling mentions, citations, and competitor presence into a single number.
- AI brand sentiment
- How AI engines characterize your brand, not just whether they mention it.
How engines work
- Entity
- A distinct thing a model recognizes, such as a company, product, or person, along with what it knows about it.
- Structured dataSchema markup
- Machine-readable markup that labels what content is, helping engines extract and trust it.
- llms.txt
- A proposed plain-text file that points AI crawlers to your most important content in Markdown.
- Retrieval-augmented generationRAG
- A method where a model fetches relevant documents at answer time and writes from them.
- Grounding
- Tying a model's answer to specific sources so claims can be traced and checked.
- Hallucination
- When a model states something false or invented with the same confidence as a fact.
- AI crawler
- A bot that fetches web pages for AI training or live retrieval, such as GPTBot or PerplexityBot.
- Zero-click search
- A search that ends without a click because the answer appears directly on the results surface.
- Knowledge graph
- A structured map of entities and the relationships between them that engines use to ground answers.
- Semantic search
- Search that matches on meaning rather than exact keywords, usually via embeddings.
- Embedding
- A numeric representation of text that lets a model compare meaning and find related content.
- Large language modelLLM
- The kind of AI model behind answer engines, trained on large text corpora to predict and generate language.